




import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union

# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...feature_extraction_utils import FeatureExtractionMixin
from ...utils import CONFIG_NAME, FEATURE_EXTRACTOR_NAME, get_file_from_repo, logging
from .auto_factory import _LazyAutoMapping
from .configuration_auto import (
    CONFIG_MAPPING_NAMES,
    AutoConfig,
    model_type_to_module_name,
    replace_list_option_in_docstrings,
)


UpperCamelCase								=	logging.get_logger(__name__)

UpperCamelCase								=	OrderedDict(
    [
        ('audio-spectrogram-transformer', 'ASTFeatureExtractor'),
        ('beit', 'BeitFeatureExtractor'),
        ('chinese_clip', 'ChineseCLIPFeatureExtractor'),
        ('clap', 'ClapFeatureExtractor'),
        ('clip', 'CLIPFeatureExtractor'),
        ('clipseg', 'ViTFeatureExtractor'),
        ('conditional_detr', 'ConditionalDetrFeatureExtractor'),
        ('convnext', 'ConvNextFeatureExtractor'),
        ('cvt', 'ConvNextFeatureExtractor'),
        ('data2vec-audio', 'Wav2Vec2FeatureExtractor'),
        ('data2vec-vision', 'BeitFeatureExtractor'),
        ('deformable_detr', 'DeformableDetrFeatureExtractor'),
        ('deit', 'DeiTFeatureExtractor'),
        ('detr', 'DetrFeatureExtractor'),
        ('dinat', 'ViTFeatureExtractor'),
        ('donut-swin', 'DonutFeatureExtractor'),
        ('dpt', 'DPTFeatureExtractor'),
        ('encodec', 'EncodecFeatureExtractor'),
        ('flava', 'FlavaFeatureExtractor'),
        ('glpn', 'GLPNFeatureExtractor'),
        ('groupvit', 'CLIPFeatureExtractor'),
        ('hubert', 'Wav2Vec2FeatureExtractor'),
        ('imagegpt', 'ImageGPTFeatureExtractor'),
        ('layoutlmv2', 'LayoutLMv2FeatureExtractor'),
        ('layoutlmv3', 'LayoutLMv3FeatureExtractor'),
        ('levit', 'LevitFeatureExtractor'),
        ('maskformer', 'MaskFormerFeatureExtractor'),
        ('mctct', 'MCTCTFeatureExtractor'),
        ('mobilenet_v1', 'MobileNetV1FeatureExtractor'),
        ('mobilenet_v2', 'MobileNetV2FeatureExtractor'),
        ('mobilevit', 'MobileViTFeatureExtractor'),
        ('nat', 'ViTFeatureExtractor'),
        ('owlvit', 'OwlViTFeatureExtractor'),
        ('perceiver', 'PerceiverFeatureExtractor'),
        ('poolformer', 'PoolFormerFeatureExtractor'),
        ('regnet', 'ConvNextFeatureExtractor'),
        ('resnet', 'ConvNextFeatureExtractor'),
        ('segformer', 'SegformerFeatureExtractor'),
        ('sew', 'Wav2Vec2FeatureExtractor'),
        ('sew-d', 'Wav2Vec2FeatureExtractor'),
        ('speech_to_text', 'Speech2TextFeatureExtractor'),
        ('speecht5', 'SpeechT5FeatureExtractor'),
        ('swiftformer', 'ViTFeatureExtractor'),
        ('swin', 'ViTFeatureExtractor'),
        ('swinv2', 'ViTFeatureExtractor'),
        ('table-transformer', 'DetrFeatureExtractor'),
        ('timesformer', 'VideoMAEFeatureExtractor'),
        ('tvlt', 'TvltFeatureExtractor'),
        ('unispeech', 'Wav2Vec2FeatureExtractor'),
        ('unispeech-sat', 'Wav2Vec2FeatureExtractor'),
        ('van', 'ConvNextFeatureExtractor'),
        ('videomae', 'VideoMAEFeatureExtractor'),
        ('vilt', 'ViltFeatureExtractor'),
        ('vit', 'ViTFeatureExtractor'),
        ('vit_mae', 'ViTFeatureExtractor'),
        ('vit_msn', 'ViTFeatureExtractor'),
        ('wav2vec2', 'Wav2Vec2FeatureExtractor'),
        ('wav2vec2-conformer', 'Wav2Vec2FeatureExtractor'),
        ('wavlm', 'Wav2Vec2FeatureExtractor'),
        ('whisper', 'WhisperFeatureExtractor'),
        ('xclip', 'CLIPFeatureExtractor'),
        ('yolos', 'YolosFeatureExtractor'),
    ]
)

UpperCamelCase								=	_LazyAutoMapping(CONFIG_MAPPING_NAMES, FEATURE_EXTRACTOR_MAPPING_NAMES)



def 				_A  (		lowerCAmelCase_	:   str     ):
     """simple docstring"""

     for module_name, extractors in FEATURE_EXTRACTOR_MAPPING_NAMES.items():
          if class_name in extractors:
               lowerCAmelCase__            =					model_type_to_module_name(lowerCAmelCase_     )

               lowerCAmelCase__            =					importlib.import_module(F'.{module_name}'  ,							"transformers.models"     )
               try:
                    return getattr(lowerCAmelCase_  ,							lowerCAmelCase_     )
               except AttributeError:
                    continue

     for _, extractor in FEATURE_EXTRACTOR_MAPPING._extra_content.items():
          if getattr(lowerCAmelCase_  ,							"__name__"  ,							lowerCAmelCase_     ) == class_name:
               return extractor

    # We did not fine the class, but maybe it's because a dep is missing. In that case, the class will be in the main
    # init and we return the proper dummy to get an appropriate error message.
     lowerCAmelCase__            =					importlib.import_module("transformers"     )
     if hasattr(lowerCAmelCase_  ,							lowerCAmelCase_     ):
          return getattr(lowerCAmelCase_  ,							lowerCAmelCase_     )

     return None



def 				_A  (		lowerCAmelCase_	:   Union[str, os.PathLike]  ,							lowerCAmelCase_	:   Optional[Union[str, os.PathLike]] = None  ,							lowerCAmelCase_	:   bool = False  ,							lowerCAmelCase_	:   bool = False  ,							lowerCAmelCase_	:   Optional[Dict[str, str]] = None  ,							lowerCAmelCase_	:   Optional[Union[bool, str]] = None  ,							lowerCAmelCase_	:   Optional[str] = None  ,							lowerCAmelCase_	:   bool = False  ,							**lowerCAmelCase_	:   Any  ,							):
     """simple docstring"""

     lowerCAmelCase__            =					get_file_from_repo(
         lowerCAmelCase_  ,							lowerCAmelCase_  ,							cache_dir=lowerCAmelCase_  ,							force_download=lowerCAmelCase_  ,							resume_download=lowerCAmelCase_  ,							proxies=lowerCAmelCase_  ,							use_auth_token=lowerCAmelCase_  ,							revision=lowerCAmelCase_  ,							local_files_only=lowerCAmelCase_  ,							)
     if resolved_config_file is None:
          logger.info(
              "Could not locate the feature extractor configuration file, will try to use the model config instead."     )
          return {}

     with open(lowerCAmelCase_  ,							encoding="utf-8"     ) as reader:
          return json.load(lowerCAmelCase_     )






class 					__lowerCamelCase			:




    """simple docstring"""

    def __init__(			self	:	int  ) ->			int:
         raise EnvironmentError(
             "AutoFeatureExtractor is designed to be instantiated "
             "using the `AutoFeatureExtractor.from_pretrained(pretrained_model_name_or_path)` method."  )


    @classmethod
    @replace_list_option_in_docstrings(SCREAMING_SNAKE_CASE__  )
    def   a (			cls	:	str  ,      SCREAMING_SNAKE_CASE__	:	List[str]  ,      **SCREAMING_SNAKE_CASE__	:	List[str]  ) ->			Any:
         lowerCAmelCase__            =					kwargs.pop("config"  ,      SCREAMING_SNAKE_CASE__  )
         lowerCAmelCase__            =					kwargs.pop("trust_remote_code"  ,      SCREAMING_SNAKE_CASE__  )
         lowerCAmelCase__            =					True

         lowerCAmelCase__      ,						lowerCAmelCase__            =					FeatureExtractionMixin.get_feature_extractor_dict(SCREAMING_SNAKE_CASE__  ,      **SCREAMING_SNAKE_CASE__  )
         lowerCAmelCase__            =					config_dict.get("feature_extractor_type"  ,      SCREAMING_SNAKE_CASE__  )
         lowerCAmelCase__            =					None
         if "AutoFeatureExtractor" in config_dict.get("auto_map"  ,      {}  ):
              lowerCAmelCase__            =					config_dict["auto_map"]["AutoFeatureExtractor"]

         # If we don't find the feature extractor class in the feature extractor config, let's try the model config.
         if feature_extractor_class is None and feature_extractor_auto_map is None:
              if not isinstance(SCREAMING_SNAKE_CASE__  ,      SCREAMING_SNAKE_CASE__  ):
                   lowerCAmelCase__            =					AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__  ,      **SCREAMING_SNAKE_CASE__  )
              # It could be in `config.feature_extractor_type``
              lowerCAmelCase__            =					getattr(SCREAMING_SNAKE_CASE__  ,      "feature_extractor_type"  ,      SCREAMING_SNAKE_CASE__  )
              if hasattr(SCREAMING_SNAKE_CASE__  ,      "auto_map"  ) and "AutoFeatureExtractor" in config.auto_map:
                   lowerCAmelCase__            =					config.auto_map["AutoFeatureExtractor"]

         if feature_extractor_class is not None:
              lowerCAmelCase__            =					feature_extractor_class_from_name(SCREAMING_SNAKE_CASE__  )

         lowerCAmelCase__            =					feature_extractor_auto_map is not None
         lowerCAmelCase__            =					feature_extractor_class is not None or type(SCREAMING_SNAKE_CASE__  ) in FEATURE_EXTRACTOR_MAPPING
         lowerCAmelCase__            =					resolve_trust_remote_code(
             SCREAMING_SNAKE_CASE__  ,      SCREAMING_SNAKE_CASE__  ,      SCREAMING_SNAKE_CASE__  ,      SCREAMING_SNAKE_CASE__  )

         if has_remote_code and trust_remote_code:
              lowerCAmelCase__            =					get_class_from_dynamic_module(
                  SCREAMING_SNAKE_CASE__  ,      SCREAMING_SNAKE_CASE__  ,      **SCREAMING_SNAKE_CASE__  )
              lowerCAmelCase__            =					kwargs.pop("code_revision"  ,      SCREAMING_SNAKE_CASE__  )
              if os.path.isdir(SCREAMING_SNAKE_CASE__  ):
                   feature_extractor_class.register_for_auto_class()
              return feature_extractor_class.from_dict(SCREAMING_SNAKE_CASE__  ,      **SCREAMING_SNAKE_CASE__  )
         elif feature_extractor_class is not None:
              return feature_extractor_class.from_dict(SCREAMING_SNAKE_CASE__  ,      **SCREAMING_SNAKE_CASE__  )
         # Last try: we use the FEATURE_EXTRACTOR_MAPPING.
         elif type(SCREAMING_SNAKE_CASE__  ) in FEATURE_EXTRACTOR_MAPPING:
              lowerCAmelCase__            =					FEATURE_EXTRACTOR_MAPPING[type(SCREAMING_SNAKE_CASE__  )]
              return feature_extractor_class.from_dict(SCREAMING_SNAKE_CASE__  ,      **SCREAMING_SNAKE_CASE__  )

         raise ValueError(
             f'Unrecognized feature extractor in {pretrained_model_name_or_path}. Should have a '
             f'`feature_extractor_type` key in its {FEATURE_EXTRACTOR_NAME} of {CONFIG_NAME}, or one of the following '
             f'`model_type` keys in its {CONFIG_NAME}: {", ".join(c for c in FEATURE_EXTRACTOR_MAPPING_NAMES.keys()  )}'  )


    @staticmethod
    def   a (			SCREAMING_SNAKE_CASE__	:	Tuple  ,      SCREAMING_SNAKE_CASE__	:	List[str]  ) ->			Union[str, Any]:
         FEATURE_EXTRACTOR_MAPPING.register(SCREAMING_SNAKE_CASE__  ,      SCREAMING_SNAKE_CASE__  )


from __future__ import annotations

lowercase    :   Dict						=			tuple[int, int, int]
lowercase    :   List[str]						=			tuple[str, str, str]


# used alphabet --------------------------
# from string.ascii_uppercase
lowercase    :   int						=			'ABCDEFGHIJKLMNOPQRSTUVWXYZ'

# -------------------------- default selection --------------------------
# rotors --------------------------
lowercase    :   Optional[int]						=			'EGZWVONAHDCLFQMSIPJBYUKXTR'
lowercase    :   Optional[Any]						=			'FOBHMDKEXQNRAULPGSJVTYICZW'
lowercase    :   str						=			'ZJXESIUQLHAVRMDOYGTNFWPBKC'
# reflector --------------------------
lowercase    :   Tuple						=			{
    'A': 'N',
    'N': 'A',
    'B': 'O',
    'O': 'B',
    'C': 'P',
    'P': 'C',
    'D': 'Q',
    'Q': 'D',
    'E': 'R',
    'R': 'E',
    'F': 'S',
    'S': 'F',
    'G': 'T',
    'T': 'G',
    'H': 'U',
    'U': 'H',
    'I': 'V',
    'V': 'I',
    'J': 'W',
    'W': 'J',
    'K': 'X',
    'X': 'K',
    'L': 'Y',
    'Y': 'L',
    'M': 'Z',
    'Z': 'M',
}

# -------------------------- extra rotors --------------------------
lowercase    :   Optional[int]						=			'RMDJXFUWGISLHVTCQNKYPBEZOA'
lowercase    :   List[Any]						=			'SGLCPQWZHKXAREONTFBVIYJUDM'
lowercase    :   Dict						=			'HVSICLTYKQUBXDWAJZOMFGPREN'
lowercase    :   List[Any]						=			'RZWQHFMVDBKICJLNTUXAGYPSOE'
lowercase    :   Optional[Any]						=			'LFKIJODBEGAMQPXVUHYSTCZRWN'
lowercase    :   Tuple						=			'KOAEGVDHXPQZMLFTYWJNBRCIUS'




def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     RotorPositionT		,    _lowerCamelCase					:     RotorSelectionT		,    _lowerCamelCase					:     str)   ->       tuple[RotorPositionT, RotorSelectionT, dict[str, str]]:






							'''simple docstring'''





							if (unique_rotsel := len(set(_lowerCamelCase))) < 3:
														__UpperCamelCase      :  Tuple       =   F'Please use 3 unique rotors (not {unique_rotsel})'
														raise Exception(_lowerCamelCase)

							# Checks if rotor positions are valid
							__UpperCamelCase  ,		__UpperCamelCase  ,		__UpperCamelCase      :  str       =   rotpos
							if not 0 < rotorposa <= len(_lowerCamelCase):
														__UpperCamelCase      :  Union[str, Any]       =   F'First rotor position is not within range of 1..26 ({rotorposa}'
														raise ValueError(_lowerCamelCase)
							if not 0 < rotorposa <= len(_lowerCamelCase):
														__UpperCamelCase      :  int       =   F'Second rotor position is not within range of 1..26 ({rotorposa})'
														raise ValueError(_lowerCamelCase)
							if not 0 < rotorposa <= len(_lowerCamelCase):
														__UpperCamelCase      :  List[Any]       =   F'Third rotor position is not within range of 1..26 ({rotorposa})'
														raise ValueError(_lowerCamelCase)

							# Validates string and returns dict
							__UpperCamelCase      :  str       =   _plugboard(_lowerCamelCase)

							return rotpos, rotsel, pbdict




def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     str)   ->       dict[str, str]:






							'''simple docstring'''





							if not isinstance(_lowerCamelCase		,    _lowerCamelCase):
														__UpperCamelCase      :  Union[str, Any]       =   F'Plugboard setting isn\'t type string ({type(_lowerCamelCase)})'
														raise TypeError(_lowerCamelCase)
							elif len(_lowerCamelCase) % 2 != 0:
														__UpperCamelCase      :  int       =   F'Odd number of symbols ({len(_lowerCamelCase)})'
														raise Exception(_lowerCamelCase)
							elif pbstring == "":
														return {}

							pbstring.replace(" "		,    "")

							# Checks if all characters are unique
							__UpperCamelCase      :  Optional[int]       =   set()
							for i in pbstring:
														if i not in abc:
																					__UpperCamelCase      :  Tuple       =   F'\'{i}\' not in list of symbols'
																					raise Exception(_lowerCamelCase)
														elif i in tmppbl:
																					__UpperCamelCase      :  Tuple       =   F'Duplicate symbol ({i})'
																					raise Exception(_lowerCamelCase)
														else:
																					tmppbl.add(_lowerCamelCase)
							del tmppbl

							# Created the dictionary
							__UpperCamelCase      :  Union[str, Any]       =   {}
							for j in range(0		,    len(_lowerCamelCase) - 1		,    2):
														__UpperCamelCase      :  Union[str, Any]       =   pbstring[j + 1]
														__UpperCamelCase      :  str       =   pbstring[j]

							return pb




def       _SCREAMING_SNAKE_CASE   (						_lowerCamelCase					:     str		,    _lowerCamelCase					:     RotorPositionT		,    _lowerCamelCase					:     RotorSelectionT = (rotora, rotora, rotora)		,    _lowerCamelCase					:     str = ""		,    )   ->       str:






							'''simple docstring'''





							__UpperCamelCase      :  List[Any]       =   text.upper()
							__UpperCamelCase  ,		__UpperCamelCase  ,		__UpperCamelCase      :  Optional[int]       =   _validator(
							    _lowerCamelCase		,    _lowerCamelCase		,    plugb.upper())

							__UpperCamelCase  ,		__UpperCamelCase  ,		__UpperCamelCase      :  Tuple       =   rotor_position
							__UpperCamelCase  ,		__UpperCamelCase  ,		__UpperCamelCase      :  List[Any]       =   rotor_selection
							rotorposa -= 1
							rotorposa -= 1
							rotorposa -= 1

							__UpperCamelCase      :  List[str]       =   []

							# encryption/decryption process --------------------------
							for symbol in text:
														if symbol in abc:
																					# 1st plugboard --------------------------
																					if symbol in plugboard:
																												__UpperCamelCase      :  Dict       =   plugboard[symbol]

																					# rotor ra --------------------------
																					__UpperCamelCase      :  Optional[int]       =   abc.index(_lowerCamelCase) + rotorposa
																					__UpperCamelCase      :  List[Any]       =   rotora[index % len(_lowerCamelCase)]

																					# rotor rb --------------------------
																					__UpperCamelCase      :  Dict       =   abc.index(_lowerCamelCase) + rotorposa
																					__UpperCamelCase      :  Any       =   rotora[index % len(_lowerCamelCase)]

																					# rotor rc --------------------------
																					__UpperCamelCase      :  str       =   abc.index(_lowerCamelCase) + rotorposa
																					__UpperCamelCase      :  Union[str, Any]       =   rotora[index % len(_lowerCamelCase)]

																					# reflector --------------------------
																					# this is the reason you don't need another machine to decipher

																					__UpperCamelCase      :  Union[str, Any]       =   reflector[symbol]

																					# 2nd rotors
																					__UpperCamelCase      :  Optional[int]       =   abc[rotora.index(_lowerCamelCase) - rotorposa]
																					__UpperCamelCase      :  Optional[Any]       =   abc[rotora.index(_lowerCamelCase) - rotorposa]
																					__UpperCamelCase      :  str       =   abc[rotora.index(_lowerCamelCase) - rotorposa]

																					# 2nd plugboard
																					if symbol in plugboard:
																												__UpperCamelCase      :  Optional[Any]       =   plugboard[symbol]

																					# moves/resets rotor positions
																					rotorposa += 1
																					if rotorposa >= len(_lowerCamelCase):
																												__UpperCamelCase      :  Any       =   0
																												rotorposa += 1
																					if rotorposa >= len(_lowerCamelCase):
																												__UpperCamelCase      :  Tuple       =   0
																												rotorposa += 1
																					if rotorposa >= len(_lowerCamelCase):
																												__UpperCamelCase      :  List[str]       =   0

        # else:
        #    pass
        #    Error could be also raised
        #    raise ValueError(
        #       'Invalid symbol('+repr(symbol)+')')
														result.append(_lowerCamelCase)

							return "".join(_lowerCamelCase)


if __name__ == "__main__":
		lowercase    :   Optional[Any]						=			'This is my Python script that emulates the Enigma machine from WWII.'
		lowercase    :   int						=			(1, 1, 1)
		lowercase    :   Optional[Any]						=			'pictures'
		lowercase    :   Optional[Any]						=			(rotora, rotora, rotora)
		lowercase    :   Optional[Any]						=			enigma(message, rotor_pos, rotor_sel, pb)

		print('Encrypted message:', en)
		print('Decrypted message:', enigma(en, rotor_pos, rotor_sel, pb))